Finite Element Analysis Simulation Research Articles

Boosting the Intelligent Development of Electromagnetic Shielding Polymer Composites by Expert Knowledge

AbstractAn intelligent process for developing electromagnetic interference (EMI) shielding composites is imperative to eliminate the escalating pollution of electromagnetic waves (EMWs). Meanwhile, integrating porous and/or layered structures with polymers is demonstrated as an effective approach. Herein, expert knowledge serves as the guidance of the Simulation‐First Strategy in designing shielding structures that incorporate MXene bubble wrap‐like aerogels (MBa‐bA), characterized by distinct bubble diameters a and densities b. The simulated EMI shielding efficiency (EMI SE) of corresponding MBa‐bA/polyethylene glycol (MBa‐bAP) composites is predicted through the finite element analysis (FEA) simulation. Subsequently, the MBa‐bAP composites are fabricated by template methods and exhibit an outstanding EMI SE of up to 83.1 dB and an ultrahigh SE of absorption (SEA) of 75.1 dB in X band at a = 10 µm and b = 0.50, perfectly aligning with the simulation outcomes. Combined with macro‐scale FEA simulation and experimental evidence, the pronounced EMWs attenuation effect, heat storage/release, and mechanical performances of MBa‐bAP composites are unequivocally substantiated. Based on these, this work proves the feasibility of the intelligent development strategy and provides a research basis for developing advanced EMI shielding materials directed by expert knowledge.

Effects of corrosion on mechanical properties of bolted porous structural panel

In this paper, polylactic acid materials combined with fused deposition molding technology were used to prepare porous structural panels. A combination of quasi-static compression experiment and finite element simulation analysis was adopted to explore effect of pitting time and concentration of dichloromethane solvent on the compression properties of porous structural panels. Results showed that surface of 100 % solvent became smooth and flat, while surface of 80 % solvent only formed a dense covering film. When specimens continues to suffer from corrosion, the single-layer specimens changed its deformation directions to a certain extent, while the instability of the two layers bolted porous structural panels gradually decreased when the corrosion damage increased. Mass concentration of 90 % was the critical point for local mechanical performance of specimens.

FINITE ELEMENT SIMULATION OF LOW-RISE SCHOOL BUILDING MODEL WITH SEISMIC LOADS INPUT

Earthquake impacts on buildings have garnered increased attention as Malaysia experiences seismic activities, notably from nearby regions like Sumatra and within areas such as Sabah. Despite this, current Malaysian design guidelines, such as BS 8110, do not fully incorporate seismic loads. This study addresses this gap by examining the structural performance of a scaled 1:8 model of a three-storey, low-rise school building under various peak ground accelerations (PGA) from 0.1g to 1.0g. Utilizing ABAQUS finite element simulation and time-history analysis, we evaluated the seismic responses, including local deformations, von Mises stress, and principal stresses. Key findings reveal a maximum structural displacement of 10.22 mm at 1.0g PGA, with significant stress concentrations observed at the column footings, highlighting critical areas for design improvement in seismic resilience.

Design of a High-Performance Bone Substitute using Finite Element Analysis and Topology Optimization

The development of bone substitutes that meet biomechanical requirements remains a significant challenge in biomedical engineering. This study integrates finite element analysis (FEA) and topology optimization to design high-performance bone substitutes optimized for load-bearing applications. Bone geometries were obtained through advanced scanning technologies, and FEA simulations were carried out using Ansys software to refine the designs. Iterative optimization enhanced the load-bearing capacity and biocompatibility while ensuring a lightweight structure. Material selection and microstructural adjustments were made to achieve optimal mechanical and biological performance. The combination of FEA and topology optimization in this research offers advancements in the design of bone substitutes, showing promising results under physiological loads and indicating strong potential for clinical applications.

Application of wet carbon black masterbatch in green mining radial tires

AbstractIn the context of environmental protection and energy consumption reduction, reducing the rolling resistance of mining machinery tires is one of the important methods to achieve the goal of green mining. This study probes the effects of wet mixing with a wet carbon black masterbatch on the rolling resistance and grounding performance of wide‐body vehicle tire treads by investigating the cross‐linking structure, rubber–filler (R–F) interaction force, and physicomechanical properties of the wet mixing rubber compounded with a wet carbon black masterbatch. The results indicate decreases in the maximum torque‐minimum torque difference, cross‐link density, and R–F interaction of the wet mixing rubber and increased filler–filler (F–F) interaction and carbon black dispersion. Meanwhile, the tensile elongation of the wet mixing rubber increases, its DIN abrasion property improves, and its Tanδ decreases at 60°C. A numerical method to estimate tire steady‐state rolling resistance is also developed. Finite element simulation analysis reveals that the steady‐state rolling resistance of the wet mixing rubber is reduced by 7.04% at 100% standard load, and its grounding performance is enhanced. By proposing a method to reduce the rolling resistance of tires, this study also provides a reference for the development of wide‐body vehicle tires.Highlights Explored the filler interaction of wet mixing rubber. Explained the low energy loss of wet mixing rubber. Proposed a new finite element method for calculating tire rolling resistance.

Simulation on the Effect of Braking Force and Brake Shoe Material Type on The Wear Rate of Railway Bogie Brake Block

The brake block in the railway bogie system is an important component in supporting the operational safety of trains, so it needs to be inspected to determine its performance and service life. A simulation-based study was conducted to predict the wear rate of railway brake block with oriented braking force (F = 25.66 kN - 29.54 kN) and different material types, namely grey cast iron with hardness 170 HBN and metallic composite with hardness 90 HRR. The method of the study was carried out by Finite Element Analysis (FEA) simulation and calculating the wear rate with the Archard wear equation to measure the comparison of the amount of wear volume that occurs on the two materials. The results of the braking ability calculation can be concluded that the different types of brake block materials can affect the ability to decelerate during the deceleration process, causing differences in stopping mileage according to the type of material, such as gray cast iron (μ = 0.30) which has an average mileage of 15 metres and metallic composite (μ = 0.21) has an average mileage of 66 metres. The wear simulation results obtained are that the grey cast iron brake block has an average wear rate of 2,8285e-08 /s which is greater than the metallic composite which is only 1,5391e-08 /s. With this data, it can be concluded that oriented to the braking force load, the metallic composite brake block material has the advantage of a longer service life than grey cast iron.

Structural performance of hybrid reinforced concrete beams containing polyvinyl alcohol fibers under thermal loads

This study focused on the efficiency of concrete beams containing polyvinyl alcohol fibers (PVA) under thermal loads. The eighteen concrete beams were reinforced with hybrid bars or a combination of GFRP bars and steel reinforcement bars (hybrid scheme). The main experimental variables were the level of temperature (25o, 300o, and 600o C), PVA fiber volume (0 %, 0.50 %, and 1.0 %), and the flexural reinforcement bars. The experimental test results are discussed in terms of the first crack load, flexural capacity, and load-deflection curves. Moreover, the initial and post-crack stiffness, ductility factor, and failure modes are discussed. The test results demonstrated a significant increase in the capacity of PVA concrete beams reinforced with hybrid reinforcement bars. At a temperature of 300o C, the inclusion of 0.50 % and 1.0 % PVA ratios improved the flexural capacities by 11 % and 24 %, respectively. Furthermore, the addition of PVA fibers enhanced the toughness by 34 % and 67 %, respectively, when compared to normal concrete beams. The results also demonstrate that using PVA fibers prevents the spalling of concrete beams after exposure to elevated temperatures. At 600 °C, beams containing 0.50 % and 1.0 % PVA fibers exhibited flexural capacities that were 9 % and 6 % higher, respectively, compared to normal concrete beams. Additionally, the inclusion of PVA fibers increased the toughness by 27 % and 21 % for the respective fiber ratios. Finally, a nonlinear finite element analysis (NLFEA) simulation was performed to verify the experimental test results and supplement experiments by predicting the results that are difficult to accomplish through experiments. With an average ratio of 1.02 between experimental and NLFEA ultimate capacity, the numerical results were an exact match of the patterns observed in the experimental results.

An attention-based architecture for predicting thermal stress on turbine blade film hole surface using partial temperature data

The thermal stress of film holes is crucial for the life of turbine blades with double-wall cooling systems. Finite Element Analysis (FEA) is widely used for thermal stress analysis, which requires the entire temperature field as input. However, only partial temperature data can be measured in engineering experiments, which is insufficient for FEA. This study proposed an attention-based deep learning architecture to map partial temperature data to film hole surface thermal stress. A thermal stress dataset with 300 samples of double-wall cooling units was constructed using conjugate heat transfer and FEA simulations and the thermal stress prediction model was trained using this dataset. Compared with the simulation results, the mean relative error (MRE) of the predicted results on the test dataset is 7.43%, and the MRE of peak thermal stress is 2.16%. The impact of the model input composed of different surface groups and sampling schemes on prediction performance was analyzed, and a reference for temperature measurement arrangement that balances accuracy and cost-effectiveness was proposed. Additionally, The impact of input noise on model performance was explored and the results demonstrate that the model trained with noise demonstrated significantly enhanced resistance to noise, and the MRE was about 8%.

Failure analysis and structural optimization of unequal-parameter metal bellows in resistance to bending and torsional composite deformation

In practical engineering applications, metal bellows are subjected to complex environmental conditions, and they usually deform under the combined effects of tension, bending and torsion. In this paper, the bending and torsion composite deformation of unequal parameter metal bellows arranged alternately by large wave and wavelet is studied. Firstly, the finite element model of metal bellows is constructed, and the finite element simulation analysis of its mechanical properties is carried out. Taking the simulation results as samples, the multi-objective structural optimization of unequal parameter metal bellows under the condition of bending and torsion composite deformation is carried out. Combined with the bending-torsion composite deformation test and fracture microscopic characterization, the bending-torsion composite deformation characteristics and fracture failure mechanism of equal-parameter metal bellows (EPMB) and unequal-parameter metal bellows (Un-EPMB) were compared and analyzed. The results show that under the same deformation conditions, compared with the EPMB, the elastic limit bending line displacement and elastic limit torsion angle displacement of Un-EPMB are increased by 52.94 %, and the bending and torsional stiffness are greatly improved, moreover, the alternating waveform arrangement led to relatively gradual stress transfer through the Un-EPMB during the bending-torsion composite deformation process, thereby reducing stress concentration. Thus, the Un-EPMB exhibited more favorable mechanical properties. Unlike in the EPMB, which underwent fracture along the grain boundary, the cracks in the Un-EPMB appeared in the middle layer and propagated to both sides in a wavelike pattern. The dimples were distributed in the middle layer of the fracture, which indicates ductile behavior.

A novel theoretical analysis method for the longitudinal cascaded piezoelectric transducer based on equivalent circuit

Abstract High power ultrasonic transducers are widely used in the fields of ultrasonic cleaning, ultrasonic welding and therapeutic ultrasound. To further improve the ultrasonic intensity and power of piezoelectric transducers for power ultrasound applications, the cascaded piezoelectric transducer have received tons of attention. The electromechanical equivalent circuit, as a classical transducer analysis method, translates the structural and mechanical parameters into the corresponding circuit parameters and helps us to better understand and analyze the performance characteristics of the transducer, which is of great significance for the design and optimization of the transducer. In this paper, a new theoretical analysis method based on the equivalent circuit is proposed for cascaded piezoelectric transducer. In this method, the equivalent circuit of each component of the longitudinal piezoelectric transducer is cascaded, and equivalent circuit is analyzed using the Kirchhoff’s law to obtain the frequency resonance equation of the piezoelectric transducer. This analysis method avoids the complex equivalent transformation of the equivalent circuit including multiple excitation sources and also obtains the vibration velocity of the piezoelectric transducer radiation surfaces, more information on the vibration characteristics of the transducer was gained from the theoretical aspect. Finally, the theoretical analysis results are compared with the finite element simulation analysis and the traditional analysis results for verification.

Design and FEA verification of high dimensional and multi-field smart soft material

Abstract We designed a sophisticated smart soft tissue material that simulates the properties of biological soft tissue and detects three-dimensional force. Inspired by electronic skin, this material uses capacitive pressure sensors and multi-layer sensor packaging. Finite element analysis and multi-field simulation were employed for structural design and verification. The study evaluated the theory and practicality of a flexible capacitive 3D force sensor for detecting pressure and shear force. Mechanical and electrical properties were confirmed through force and electric field simulations. The 3D force detection method proved feasible, achieving sensitivity levels of 10−4 kPa −1 in the X and Y directions, and 10−3 kPa −1 in the Z direction, demonstrating the effectiveness of our design.

Efficiency enhancement of bicycle anti-lock braking systems (ABS): Design and optimization of solenoid actuators through finite element analysis and performance simulation

The rising popularity of cycling underscores the need for enhanced safety, particularly under challenging braking conditions. This study introduces a novel high-power switch valve designed explicitly for Bicycle Hydraulic Disc Brakes (BHDBs), incorporating Hydraulic Anti-lock Braking Systems (ABS). Comprehensive Finite Element Analysis (FEA) modeling and subsequent optimization of an existing solenoid valve’s internal geometry were performed through 2D and 3D simulations to evaluate magnetic flux. The improved design achieved a maximum output force of 280 N with a linear stroke of approximately 3.5 mm. Notably, the enhanced system exhibited a 28% reduction in required current, from 5.0 to 3.6 A, a result validated through LabVIEW-equipped custom tests, which stress the credibility of the research. This study underscores significant advancements in high-power switch valves for BHDBs, promising enhanced braking efficiency and safety in high-performance, battery-powered bicycles. These findings not only promise enhanced safety for cyclists but also suggest the potential for broader application in energy-efficient and sustainable bicycle ABS technology, contributing to improved cyclist safety without compromising the environmental and health benefits of cycling. The potential impact of this research extends beyond the immediate context, offering insights that could be applied to other areas of technology and safety.

Spatial-confined effect of CuOx microneedles bundles on TiO2 nanotubes: Reinforcing the adsorption and enrichment of ultralow concentration nitrate for efficient NH3 electrosynthesis

Nitrate (NO3−) Electroreduction to produce NH3 offers an alternative approach to sustainable production of NH3. Yet it remains challenging to simultaneously improve the adsorption and enrichment of low-concentration NO3−. Here, bundles of CuOx microneedles on TiO2 nanotubes (NTs) were developed by a spatial-confined electrodeposition strategy, achieving 87.7 % or 98.4 % NH3 FE at −0.25 V or −0.45 V vs RHE in 2 or 10 mM NO3− electrolytes, respectively. Both in-situ spectroscopy and finite element analysis simulation demonstrated that CuOx microneedle bundles and its interface between TiO2 NTs not only greatly improve the enrichment of low concentration NO3− and its derived-NO2− and the diffusion of NH3 product, but also enhance the adsorption of NO2− and H2O to facilitate the hydrodeoxygenation of NO3− as well as inhibit hydrogen evolution reaction competition. This work will provide a promising avenue to develop electrocatalysts to realize efficient catalytic conversion of reactants at low concentrations.

The cation exchange driving multi-phase regulation in Co7Fe3/Co@NC for enhanced broadband electromagnetic wave absorption

Phase engineering offers distinctive advantages in designing efficient electromagnetic wave (EMW) absorbers. The manipulation of the interaction and arrangement of different multi-phase systems enables the achievement of more precise EMW absorption. However, the transition mechanism from single metal phases to metal/alloy phases has not yet been fully revealed. Here, we employ multiphase engineering driven by cation exchange reactions to finely control the proportion of Co/Co7Fe3 phases and regulate electromagnetic parameters. The introduction of cavities and heteroatoms through cation exchange enables optimized defect distribution and composition, which enhances both impedance matching and electromagnetic attenuation capabilities. Specifically, we yield hollow Co7Fe3/Co@N-doped carbon (H-Co7Fe3/Co@NC) embedded in high-crystallinity graphite carbon after high-temperature pyrolysis, which promotes significant electron transfer between phases, thus enhancing conduction and polarization losses. H-Co7Fe3/Co@NC exhibits ultra-strong reflection loss (RL) of −59.70 dB at 9.37 GHz and achieves broadband absorption of 6.01 GHz at 2.1 mm. This study highlights the influence of Co7Fe3/Co heterogeneous structures on absorption performance and validates the electromagnetic response mechanism of multi-phase heterostructures through COMSOL finite element simulation analysis. Thus, this work paves the way for applying multi-phase engineering driven by cation exchange reactions for advanced absorbers.

Damage Detection and Localization Methodology Based on Strain Measurements and Finite Element Analysis: Structural Health Monitoring in the Context of Industry 4.0

This paper investigates the integration of Structural Health Monitoring (SHM) within the frame of Industry 4.0 (I4.0) technologies, highlighting the potential for intelligent infrastructure management through the utilization of big data analytics, machine learning (ML), and the Internet of Things (IoT). This study presents a success case focused on a novel SHM methodology for detecting and locating damages in metallic aircraft structures, employing dimensional reduction techniques such as Principal Component Analysis (PCA). By analyzing strain data collected from a network of sensors and comparing it to a baseline pristine condition, the methodology aims to identify subtle changes in local strain distribution indicative of damage. Through extensive Finite Element Analysis (FEA) simulations and a PCA contribution analysis, the research explores the influence of various factors on damage detection, including sensor placement, noise levels, and damage size and type. The findings demonstrate the effectiveness of the proposed methodology in detecting cracks and holes as small as 2 mm in length, showcasing the potential for early damage identification and targeted interventions in diverse sectors such as aerospace, civil engineering, and manufacturing. Ultimately, this paper underscores the synergistic relationship between SHM and I4.0, paving the way for a future of intelligent, resilient, and sustainable infrastructure.

A framework for rapid fatigue hotspot localization and damage assessment of plate with multiple holes based on the fatigue damage response spectrum method

AbstractThis paper proposes a novel framework for the random vibration fatigue assessment of thin‐walled plate with multiple holes based on the fatigue damage response spectrum method. Compared with other frequency‐domain evaluation methods, this framework fully exploits the dynamic characteristics of complex structures, decoupling the external excitation characteristics from the spatial characteristics of the structural response. This approach significantly enhances evaluation efficiency by avoiding the complex calculations associated with stress response spectral moments. The proposed method is employed to evaluate the contribution of each mode to the overall damage, additionally, the stress mode shapes are used to identify and refine the mesh around fatigue hotspots. Modal damage contribution factors are proposed to identify the key modes. By leveraging both structural dimension reduction and modal reduction techniques, the proposed framework can swiftly and accurately locate fatigue hotspots within complex structures and conduct precise fatigue assessments using the Absolute Sum ‐ Square Root of the Sum of Squares hybrid method. Finite element simulation analysis is conducted on a single‐lap structure containing numerous circular openings, validating the accuracy and efficiency of the proposed stochastic vibration fatigue assessment.

Assessment of residual stress evolution in glass-to-metal seals amid heating process: Insights from in situ observations and finite-element analysis

The dynamics of residual stress (RS) within glass-to-metal (GTM) seals play a crucial role in their operational efficacy, with the progression of RS in response to temperature variations being a critical aspect in engineering applications. This research utilizes fiber Bragg grating sensors and temperature-calibrated photoluminescence spectroscopy techniques for the in situ monitoring of RS changes within GTM seals during heating. Initially, the glass body exhibited a compressive stress of −203 MPa, while the stress in the glass close to the interface was −367 MPa at room temperature. With increasing temperature, RS within both the glass body and in the glass close to the interface transitions through three distinct phases: a near-linear decrease, a rapid decrease, and a shift from compressive to tensile stress. By 540 °C, tensile stresses of approximately 11 MPa within the glass body and 36 MPa in the glass close to the interface were observed. The study elucidates that RS evolution is intricately linked not only to the thermal expansion properties of the constituent materials but also to the β-relaxation phenomenon within the glass structure and the presence of an oxide layer at the interface. Finite-element analysis simulations were conducted to corroborate the experimental findings, illustrating a congruent RS evolution pattern and delineating the transition from a compressive to a tensile state. This investigation provides empirical data and analytical insights concerning the management of RS in GTM seals, underscoring the significance of RS control in maintaining seal integrity.

Highly stretchable and flexible kirigami patterned silver electrodes for wearable electronics

The next-generation wearable devices require highly stretchable and stable conductive electrodes. Accordingly, in this study, kirigami patterned silver electrodes were designed using finite element analysis (FEA) simulation to obtain an outstanding stretchable structure. Silver patterned electrodes have excellent stretchability owing to utilizing metamaterials and implementing specific patterning. Patterned Ag electrodes were fabricated on flexible polyurethane (PU) substrate, which showed acceptable stretching results at higher strains than Ag electrodes without any pattern. The resistance change (ΔR/R0) during the stretching test was less than 7, when the electrode was stretched up to 50 % strain. In addition to stretching, other mechanical tests, such as the stretching fatigue, bending fatigue, rolling, folding, and twisting tests, were conducted, exhibiting less change in resistance which indicates the durability of the kirigami patterned Ag architecture for manufacturing stretchable electrodes which are applicable to wearable sensors. The patterned silver electrodes developed in this study were used as a wearable temperature sensor and a stretchable interconnector. A wearable temperature sensor with patterned electrode was produced to assess the temperature-sensing properties of the proposed electrode architecture with resistance changes for human wearable applications. In addition, a stretchable interconnector examines its performance when connected to a light emitting diode.

(Invited) Architectural Refinement in Core-Shell Ni/Ni(OH)2 Nanowires Array for Enhanced Supercapacitor Performance - A Comprehensive Electrochemical and Finite Element Study

We investigated the electrochemical performance and effect of different aspect ratios of core-shell Ni/Ni(OH)2 nanowires arrayed in an asymmetric supercapacitor with graphene flakes. We created thenanowires with diameters of 35 nm, 100 nm, 150 nm and different height using electrodeposition with help of Anodic Alumina Oxide template, allowing us to regulate their dimensions accurately. We identified an intriguing trend: supercapacitor performance first rises with nanowire height, but then steadily drops when a critical threshold is reached. We used Finite Element Analysis (FEA) to corroborate our experimental results and uncover the underlying electrochemical processes in order to better explain and comprehend this phenomenon. According to the FEA simulations, the nanowire length effects the distribution and accessibility of ionic species surrounding the nanowire array, which influences the charge storage and transfer processes. Figure 1

Rapid detection of SARS-CoV-2 with a mobile device based on pulse controlled amplification

In the past, vast research has been conducted on biosensors and point-of-care (PoC) diagnostics. Despite rapid advances especially during the SARS-CoV-2 pandemic in this research field a low-cost molecular biosensor exhibiting the user-friendliness of a rapid antigen test, and also the sensitivity and specificity of a PCR test, has not been developed yet. To this end we developed a novel microfluidics based and handheld PoC device, that facilitates viral detection at PCR sensitivity and specificity in less than 40 min, including 15 min sample preparation. This was attained by incorporation of pulse controlled amplification (PCA), a method which uses short electrical pulses to rapidly increase the temperature of a small fraction of the sample volume. In this work, we present a low-cost PCA device with a microfluidic consumable intended for the use in a decentralized or home-setting. We used finite element analysis (FEA) simulations to display the fundamental principle and highlight the critical parameter dependency of PCA, such as pulse length and resistor shape. Furthermore, we integrated a simple and fast workflow for sample preparation and evaluated the limit of detection (LoD) for SARS-CoV-2 viral RNA, which is 0.88 copies/μL (=44 copies/reaction), and thus, comparable to conventional RT-qPCR. Additionally, target specificity of the device was validated. Our device and PCA approach enables cost-effective, rapid and mobile molecular diagnostics while remaining highly sensitive and specific.